Previous Knowledge Research Articles

Does Exposure to Televised Debates Change the Weight of Different Criteria for Candidate Assessment? A Quasi-Experiment in the Context of the 2014 Spitzenkandidaten Debate

In this article, we show how exposure to debates primes specific candidate assessments as key factors of candidate appraisal. To fulfil this goal, we rely on quasi-experimental data collected in 24 European Union Member States and focus on a debate starred by largely unknown candidates (the 2014 European Spiztenkandidaten) engaged in a remarkably invisible campaign. Our results show that candidate perceptions become much more important factors of general candidate appraisal after the debate in the case of three out of the five lead candidates, namely those whose image benefitted from their participation in the debate. In several cases, personal likeability became more important in the general assessment of the Spitzenkandidaten, but there was also an increased relevance of the perceptions of leadership strength (Keller) and quality of the ideas to stimulate the European economy (Schulz and Tspiras). Moreover, in the cases of Schulz, Keller, and Tsipras, post-exposure candidate perceptions impacted more their general appraisal by participants without previous knowledge of them than by those who claimed to know them before the debate. Interestingly, leadership strength appraisal was more relevant for the former than for the latter participants. In short, by unveiling these patterns, this article not only provides evidence of the priming effects of debate exposure but also illustrates how such effects may vary according to citizens’ previous knowledge and the candidates’ general performance in the debate.

Characterization and active component identification of Premna herbacea roxb. root extract reveals anti-inflammatory effect and amelioration of imiquimod induced psoriasis via modulation of macrophage inflammatory response

Background1-2.88% of human populations are affected by psoriasis, one type of chronic inflammatory skin disease. Skin thickenings, erythema, scaling in skin are the most important symptoms of psoriasis. There are renewed interests amongst scientists in studying anti-inflammatory property of the plant extracts due to lower side effects and cost effectiveness. There are few reports suggesting anti-inflammatory activity of Premna herbacea roxb. but lacks systematic evaluation of these properties. MethodsWe, initially tested the anti-inflammatory activity of crude root methanolic extract in vitro, where it significantly reduced LPS generated ROS in splenic macrophages. We further tested the TLC and HPLC fraction in order to find active ingredient in Premna herbacea roxb. root extract that ameliorated the chronic inflammation of skin and performed GC-MS and LC-MS studies to identify active component. Upon finding significant anti-inflammatory effect of the crude root extract in vitro, We studied the efficacy of the Premna herbacea roxb. root extract in Imiquimod induced psoriasis like skin inflammation in male BALB/C mice that closely resembles human psoriasis. Immunophenotyping, Cytokine productions were observed by flow cytometry, status of gene expression was done by Real time PCR and nuclear co-localization was studied by confocal microscopy. ResultsWe observed progressive increase in signs and symptoms of the disease in imiquimod treated diseased animals but the Premna herbacea roxb. Root Methanolic Extract (PHRME) reduced the thickening of the skin, redness and scaling in these animals. In our study, along with progression of the disease, the production of macrophages increases and with the application of PHRME, the percentage of macrophages have reduced. ConclusionAs per the previous Indigenous traditional knowledge regarding use of Premna herbacea roxb. against inflammatory disorder and lack of detail mechanistic study of the crude root extract prompted us to elucidate the efficacy of the root extract in vitro and in vivo psoriatic mice model. For the first time we have identified three putative bioactive active components (5‑hydroxy-7-methoxyflavanone, 3-Hydroxy-7,8,2′,3′-tetramethoxyflavone, 2,4′,6′-trimethoxy chalcone) from Premna herbacea root methanolic extract (PHRME) and we suggest PHRME and purified active fractions influence NFκB and COX2 signaling pathway to suppress inflammatory conditions. All of the purified components show strong binding efficiency in our molecular docking analysis. Our study also suggests that Premna herbacea roxb. root extract may be explored as cost effective alternative for established treatment regimen as our study also indicates low side effect of the extract against pre-clinical psoriatic model.

Statistical mechanics of continual learning: Variational principle and mean-field potential.

An obstacle to artificial general intelligence is set by continual learning of multiple tasks of a different nature. Recently, various heuristic tricks, both from machine learning and from neuroscience angles, were proposed, but they lack a unified theory foundation. Here, we focus on continual learning in single-layered and multilayered neural networks of binary weights. A variational Bayesian learning setting is thus proposed in which the neural networks are trained in a field-space, rather than a gradient-ill-defined discrete-weight space, and furthermore, weight uncertainty is naturally incorporated, and it modulates synaptic resources among tasks. From a physics perspective, we translate variational continual learning into a Franz-Parisi thermodynamic potential framework, where previous task knowledge serves as a prior probability and a reference as well. We thus interpret the continual learning of the binary perceptron in a teacher-student setting as a Franz-Parisi potential computation. The learning performance can then be analytically studied with mean-field order parameters, whose predictions coincide with numerical experiments using stochastic gradient descent methods. Based on the variational principle and Gaussian field approximation of internal preactivations in hidden layers, we also derive the learning algorithm considering weight uncertainty, which solves the continual learning with binary weights using multilayered neural networks, and performs better than the currently available metaplasticity algorithm in which binary synapses bear hidden continuous states and the synaptic plasticity is modulated by a heuristic regularization function. Our proposed principled frameworks also connect to elastic weight consolidation, weight-uncertainty modulated learning, and neuroscience-inspired metaplasticity, providing a theoretically grounded method for real-world multitask learning with deep networks.

Quality of housing services in the student residential areas of Osun State University, Osogbo campus, Nigeria

PurposeThe purpose of this paper is to evaluate the quality of housing services in the students’ residential areas (SRAs) of Osun State University, Osogbo campus.Design/methodology/approachEighty-eight hostels were systematically sampled and questionnaires were administered to students' representatives from each of the sampled hostels. Also utilized was a physical observation of the hostels. Data obtained include the socioeconomic characteristics of the students, characteristics of housing units in the SRAs and condition of housing services in the SRAs.FindingsAbout 40% of the residents are fresh students with no previous knowledge of the housing condition of their hostels. Also, about 50% of the accommodation in the SRAs is within the range of #51,000 – #100,000 per annum (about 200–400 US Dollars). With this high price, about 65% of the hostels are occupied with not less than two squatters. While housing services such as electricity are reportedly high, the quality of hostel services in the study area depends on the housing unit's cost.Social implicationsIn the social context, the paper identifies the implications of the quality of housing services on students' health and associated risks. The study, among others, recommends the development of a regulatory framework for the control of the rental value of hostels, basic facilities in the hostels and the number of students in a room.Originality/valueThis research, unlike previous researches, gives an insight into quality of housing services in tertiary institutions in the country.

Clinical and Autonomic Profile, and Modified Calgary Score for Children and Adolescents with Presumed Vasovagal Syncope Submitted to the Tilt Test.

In the pediatric population, syncope is mainly from vasovagal (VVS) origin. Its evaluation must be done by clinical methods, and the tilt test (TT) can contribute to the diagnosis. To analyze the clinical profile, Calgary and modified Calgary scores, response to TT and heart rate variability (HRV) of patients aged ≤ 18 years with presumed VVS. To compare the variables between patients with positive and negative responses to TT. Observational and prospective study, with 73 patients aged between 6 and 18 years, submitted to clinical evaluation and calculation of scores without previous knowledge of the TT. It was done at 70º under monitoring for HRV analysis. P-value < 0.05 was the statistical significance criterion. Median age was 14.0 years; 52% of participants were female, 72 had Calgary ≥ -2 (mean 1.80), and 69 had modified Calgary ≥ -3 (mean 1.38). Prodromes were observed in 59 patients, recurrence in 50 and trauma in 19. The response to TT was positive in 54 participants (49 vasovagal, with 39 vasodepressor responses), with an increase in the low frequency (LF) component and a decrease in the high frequency (HF) component (p < 0,0001). In the supine position, LF was 33.6 in females and 47.4 in normalized units for males (p = 0.02). When applying the operating characteristic curve for positive TT, there was no statistical significance for HRV and scores. Most children and adolescents with a presumed diagnosis of VVS presented a typical clinical scenario, with a Calgary score ≥ -2, and a predominant vasodepressor response to TT. Greater sympathetic activation was observed in the supine position in males. Calgary scores and sympathetic activation did not predict the response to TT.

Portfolio Performance of European Target Prices

This paper examines the performance of actively managed portfolios constructed using target price recommendations provided by analysts. We propose two methods for constructing portfolios based on Bloomberg’s 12-month target price consensus, which serves as a signal to buy or sell assets. Using a sample of 50 European stocks over a 19-year period (from 1 April 2004 to 31 March 2023), we compare the performance of target-price-based portfolios to traditional alternatives, such as a naïve homogeneous portfolio and the Eurostoxx 50 index, as well as to passive portfolios based on average recommendations. We also look into the mean-variance efficiency of these portfolios and find that all exhibit similar levels of efficiency, which are well below the performance of the theoretical tangent portfolios. Our results indicate that target-price-based portfolios show performance very close to that of the naïve homogeneous portfolio. Even the passive “average” target price portfolios, which require previous knowledge of targets for the entire investment period, are unable to outperform the naïve portfolio. Our main findings are based on a 15-year investment horizon but are robust when considering smaller maturities and out-of-sample data. We also investigate the impact of rebalancing on portfolio performance and find that it does pay off in the long run (over an 8-year investment period), but the frequency of rebalancing matters. Rebalancing only once a year is as detrimental to performance as not rebalancing at all. However, it is unclear whether the transaction costs associated with frequent rebalancing would offset any relative outperformance. Overall, our study contributes to the literature on portfolio management and market efficiency by demonstrating the potential benefits and limitations of using target price recommendations to construct portfolios, highlighting the importance of carefully considering rebalancing strategies to achieve optimal performance.

English language proficiency, prior knowledge, and student success in an international Chinese accounting program

International student exchange programs have gained popularity as a means to increase enrollments, support international academic partnerships, and improve student preparedness for globalized work environments. However, the relationships between English language proficiency, cultural intelligence, teamwork, self-efficacy, academic success, and other factors within these programs are not clear. This study investigates the correlations among international accounting students’ English language proficiency, accounting knowledge, and academic performance in a transnational education program in mainland China. Data were obtained from academic records of 104 accounting students enrolled in the program. A quantitative measuring of the Pearson correlation statistical tests were employed to measure the relationships between English language proficiency and academic performance, as well as between previous accounting knowledge and academic success. The results indicate a statistically significant relationship between English language proficiency and academic performance, and between previous accounting knowledge and academic success. This study has significant implications for transnational education programs, academic institutions, and policymakers and provides insights into effective strategies for enhancing the quality of transnational education programs and promoting the internationalization of higher education.

Fracture identification in reservoirs using well log data by window sliding recurrent neural network

Detecting fractures using well logs can be difficult due to the complex response of conventional logs. To address this issue, a novel method called Fracture Identification by window sliding and recurrent neural network (FIsr) is proposed. FIsr uses window sliding to generate sequence image data for training a bidirectional recurrent neural network (BiLSTM) classifier, with columns selected from both conventional and reconstructed logs. Undersampling is applied to balance the data, as the number of fracture samples is much smaller than nonfracture samples. BiLSTM extracts features from the sequence data in two directions, considering label correlations and detecting local log anomalies caused by fractures. The prediction for each sample is based on multiple overlapping sequence images to reduce uncertainties. The proposed method is validated using a dataset from carbonate reservoirs of the Asmari Formation in the Middle East, with an accuracy of 95% and recall and precision metrics exceeding 90%. A blind well test shows that FIsr can detect all fracture zones, and the distribution of fractures along the well trajectory confirms previous knowledge of the area. The study also discusses the influence of factors in FIsr.

Architecture towards Technology—A Prototype Design of a Smart Home

Humanity’s way of life has been irreversibly transformed by new technological advancements during the past decades. Although such technological innovations have been gradually transposed into architecture, their full integration is not yet achieved. This article addresses the issue of incorporating cutting-edge technologies (such as smart thermostats, lighting sensors, security cameras, remote commands, graphic user interfaces, smartphones, mobile apps, gestures, voice commands, etc.) into urban small-scale residential architecture, in the future evolution context. For this purpose, a methodology was conceived that the main concepts regarding automation and information networks were researched, as well as their practice in some reference architecture cases. The guidelines for the prototype architectonic design were defined based on the previous knowledge acquired. Then, a prototype design of an intelligent home was iteratively developed as a machine for living in constant change. It was expected to contribute to increasing and disseminating knowledge in these fields, explaining their benefits and limitations. The prototype design presented in this article contributes to sensitizing architecture professionals to the importance of integrated and systematized thinking in all procedures of a smart home design.

How do we choose whom to support? Different approaches to selection criteria in business pre-incubation

Purpose The purpose of this study was to gain a deeper understanding of the selection criteria used in preincubation programs. Particular focus has been placed on examining the exclusive and inclusive nature of these criteria, and how they relate to both egalitarian and utilitarian considerations. Design/methodology/approach The study used two data sources: archival available online data and semi-structured interviews. Forty-nine preincubation programs were examined, with 19 representatives interviewed. The data was analyzed using content analysis to understand the access and selection criteria applied at the preincubation stage. Findings The goals of preincubation programs vary, including developing students’ competencies, creating new companies or achieving the goals of the corporation that sponsored the program. preincubation programs use three levels of selection criteria, including entry criteria, the potential of the submitted idea and team and the personal characteristics and competencies of the applicants. The entry criteria varied across programs, with some programs being open only to university employees and students, while others were open to the public. The study found that the majority of preincubation programs used a combination of both egalitarian and utilitarian motivations in their selection criteria. Practical implications The criteria used to evaluate applications flowing into preincubation should be strongly related to the goals that preincubation is supposed to achieve. It is essential to consider that, contrary to previous knowledge, this process is not only aimed at supporting the creation of new businesses. Originality/value To the best of the author’s knowledge, this is the first study that analyzes the approach to selection criteria in preincubation programs with such diverse goals and in different countries as well as expanding the understanding of the criteria used at different stages of the incubation process and relating to the inclusiveness in entrepreneurship.

ReCom: A semi-supervised approach to ultra-tolerant database search for improved identification of modified peptides

Open-search methods allow unbiased, high-throughput identification of post-translational modifications in proteins at an unprecedented scale. The performance of current open-search algorithms is diminished by experimental errors in the determination of the precursor peptide mass. In this work we propose a semi-supervised open search approach, called ReCom, that minimizes this effect by taking advantage of a priori known information from a reference database, such as Unimod or a database provided by the user. We present a proof-of-concept study using Comet-ReCom, an improved version of Comet-PTM. Comet-ReCom increased identification performance of Comet-PTM by 68%. This increased performance of Comet-ReCom to score the MS/MS spectrum comes in parallel with a significantly better assignation of the monoisotopic peak of the precursor peptide in the MS spectrum, even in cases of peptide coelution. Our data demonstrate that open searches using ultra-tolerant mass windows can benefit from using a semi-supervised approach that takes advantage from previous knowledge on the nature of protein modifications. SignificanceThe present study introduces a novel approach to ultra-tolerant database search, which employs prior knowledge of post-translational modifications (PTMs) to improve identification of modified peptides. This method addresses the limitations related to experimental errors and precursor mass assignation of previous open-search methods. Thus, it enables the study of the biological significance of a wider variety of PTMs, including unknown or unexpected modifications that may have gone unnoticed using non-supervised search methods.

Scratch as an Environment for Learning the Coordinate System by Elementary School Students

The focal point of mathematics education research is to comprehend how students develop and consolidate their abstract mathematical knowledge. As goal of this research, the focus was on exploring the processes that sixth-grade students used to construct mathematical concepts linked to the coordinate system. In this study, a group of eight students was selected for research purposes. Video recordings were used to collect data through observations. The Abstraction in Context (AiC) framework was utilized to analyze the students’ processes that took place within the Scratch environment. The research findings suggested that the grade six students successfully constructed most of the anticipated knowledge components, consolidated their previous knowledge related to the zero concept, and began to develop new ones. Specifically, the students were able to construct the concept of zero as a number that is neither positive nor negative, as well as comprehend the X and Y axes.

Towards more sustainable higher education institutions: Implementing the sustainable development goals and embedding sustainability into the information and computer technology curricula

Lately, there has been a rising trend towards integrating sustainability issues and implementing sustainable development (SD) goals into higher education, especially in the Information and Communication Technology (ICT) field. This paper presents the challenges of the introduction of education for sustainability in higher education institutions, analyzes how these challenges could be addressed, and records the essential principles that can guide the incorporation of SD education in higher education. At the same time, this paper advocates the concept of sustainability integration into undergraduate ICT curricula and provides indications for developing ICT curricula that integrate sustainability issues. This paper also examines the contribution of education to the environmental awareness of the students at a Greek University while it captures their perceptions regarding the necessity for the inclusion of sustainability in the ICT curricula. The results are based on the processing of two questionnaires (pre-test and post-test data) distributed during two lectures regarding sustainability at a two-week interval. The findings of the study prove that the direct effect of the educational intervention on the intention of the students to engage in sustainability is significant. Furthermore, it is observed that students show a positive attitude towards integrating sustainability issues into their ICT education. In addition, although students had a deficient level of understanding of the concept of SD goals before the intervention, they showed a significant increment in their previous knowledge regarding sustainability and the environmental impact of ICT studies. The research also reveals that the students are not satisfied with the engagement of the university towards sustainability, and they propose various awareness activities to support their engagement with sustainability issues in an inclusive manner.

Science learning in 3- and 5-year-old children in the same free-choice learning environment on plant diversity

This study responds to the need to produce inviting learning environments that help to build intentional science learning in early childhood education. We present a free-choice science learning environment on plant diversity in the fall. From the moment it was implemented, we analyzed whether children of different educational levels acted in accordance with the objectives put forth in each activity of the environment when they are given free choice. We also explored the potential relationship between achieving the stated objectives and social interactions. The participants were 13 three-year-old children and 14 five-year-old children. The free-choice sessions were video recorded and supplemented with notes taken by three researchers in a field notebook. From the records, we categorized the data according to the actions we expected of the children in each activity, related to how they interacted with the materials and the social interactions that emerged. The results show the influence of social and material interactions, as well as the children’s previous knowledge, in attaining the objectives laid out in the design. Based on these results, we propose some principles and guidelines for designing, implementing and evaluating these learning environments in early childhood education, as well as future lines of research.

The green adolescent: The joint contribution of personality and divergent thinking in shaping pro-environmental behaviours

The ongoing environmental deterioration challenges present and forthcoming generations to adopt more suitable behaviours to avoid catastrophic consequences for Earth's ecosystem. This demanding scenario has raised several questions about human activities, leading to exploring the intrapersonal factors involved in pro-environmental behaviours (PEBs). In a sample of 146 late adolescents (Mage = 19.91 years, SDage = 1.31 years, 68.5% females), the current research addressed the extent to which the Big Five personality traits predict PEBs through the effect of fluency and creativity of divergent thinking (DT). Results revealed that not only openness but also extraversion and agreeableness were indirectly associated with PEBs through the mediation of DT creativity. This study extended previous knowledge about the impact of personality on green behaviours, suggesting that adolescents must invest in and increase their DT competencies to enhance their own disposition toward pro-environmental practices. Implications, limitations, and future research directions were discussed.

Adaptive Finite-Time Trajectory Tracking Control for Coaxial HAUVs Facing Uncertainties and Unknown Environmental Disturbances

In this paper, the problems of system design, dynamic modeling, and trajectory tracking control of coaxial hybrid aerial underwater vehicles (HAUVs) with time-varying model parameters and composite marine environment disturbances are investigated. It is clear that a stable transition between different media remains a challenge in the practical implementation of amphibious tasks. For HAUVs, accurate dynamic modeling to describe complex dynamic variations during vehicle takeoff from underwater to air is a huge challenge. Meanwhile, due to the rapid changes in model parameters and the external environment, vehicles are likely to fall into the sea during the cross-domain process. An integrated continuous dynamic model considering hydrodynamic changes is established by introducing a linear switching coefficient during the process of trans-medium motion. A nonsingular fast terminal sliding-mode control (NFTSMC) algorithm combined with adaptive technology is used to design the position and attitude of the controller. With no previous knowledge of external interferences and lumped uncertainties of the HAUV, the adaptive NFTSMC (ANFTSMC) algorithm achieves the control objectives; at the same time, the inherent chattering problems of sliding mode control (SMC) are weakened. The finite-time stability of the global system is proven strictly using a series of mathematical derivations based on Lyapunov theory. The effect of the controller applied is analyzed through a series of simulations with representative working conditions. The results show that the proposed ANFTSMC can realize a “seamless” air–water trans-medium process, which proves the superiority and robustness of the proposed control algorithm.

Biochemical characterization of GAF domain of free-R-methionine sulfoxide reductase from Trypanosoma cruzi

Trypanosoma cruzi is the causal agent of Chagas Disease and is a unicellular parasite that infects a wide variety of mammalian hosts. The parasite exhibits auxotrophy by L-Met; consequently, it must be acquired from the extracellular environment of the host, either mammalian or invertebrate. Methionine (Met) oxidation produces a racemic mixture (R and S forms) of methionine sulfoxide (MetSO). Reduction of L-MetSO (free or protein-bound) to L-Met is catalyzed by methionine sulfoxide reductases (MSRs). Bioinformatics analyses identified the coding sequence for a free-R-MSR (fRMSR) enzyme in the genome of T. cruzi Dm28c. Structurally, this enzyme is a modular protein with a putative N-terminal GAF domain linked to a C-terminal TIP41 motif. We performed detailed biochemical and kinetic characterization of the GAF domain of fRMSR in combination with mutant versions of specific cysteine residues, namely, Cys12, Cys98, Cys108, and Cys132. The isolated recombinant GAF domain and full-length fRMSR exhibited specific catalytic activity for the reduction of free L-Met(R)SO (non-protein bound), using tryparedoxins as reducing partners. We demonstrated that this process involves two Cys residues, Cys98 and Cys132. Cys132 is the essential catalytic residue on which a sulfenic acid intermediate is formed. Cys98 is the resolutive Cys, which forms a disulfide bond with Cys132 as a catalytic step. Overall, our results provide new insights into redox metabolism in T. cruzi, contributing to previous knowledge of L-Met metabolism in this parasite.

Mushroom β-glucans: application and innovation for food industry and immunotherapy.

Among the most important sources of β-glucans are edible and medicinal mushrooms. These molecules are components of the cellular wall of basidiomycete fungi (mushrooms) and can be extracted even from the basidiocarp as the mycelium and its cultivation extracts or biomasses. Mushroom β-glucans are recognized by their potential effects as immunostimulants and immunosuppressants. They are highlighted as anticholesterolemic, anti-inflammatory, adjuvant in diabetes mellitus, mycotherapy for cancer treatment, as well as adjuvants for COVID-19 vaccines. Due to their relevance, several techniques of β-glucans extraction, purification, and analysis have already been described. Despite the previous knowledge of β-glucans' benefits for human nutrition and health, the main information about this topic refers to the molecular identification, properties, and benefits, as well as their synthesis and action on cells. Studies on biotechnology industry applications (product development) and the registered products of β-glucans from mushrooms are still limited and more common for feed and healthcare. In this context, this paper reviews the biotechnological production of food products containing β-glucans from basidiomycete fungi, focusing on food enrichment, and presents a new perspective on fungi β-glucans' use as potential immunotherapy agents. KEY POINTS: • Mushrooms' β-glucans for product development in the biotechnology industry • Biotechnological production of food products containing mushrooms' β-glucans • Basidiomycete fungi β-glucans are used as potential immunotherapy agents.

Design and implementation of a game-based activity to promote learning of game theory

Game theory, an interdisciplinary field that explores interactions among entities in strategic scenarios, is paramount for understanding how individuals make decisions in interactive situations. This paper outlines the development and evaluation of a playful exercise to facilitate understanding fundamental concepts such as dominant and dominated strategies and Nash equilibrium, employing a 'design thinking' methodology. An empirical evaluation was conducted with 76 Industrial Engineering students from the Universidad Industrial de Santander, dividing them into four teams representing companies vying for customers. The teams assessed payoff matrices and made marketing decisions, utilizing a colored die to eliminate non-advantageous strategies. Findings indicate a significant increase in interest in game theory, with 86% of participants expressing a preference for this method compared to conventional classes. Furthermore, 81% desired to incorporate this activity into their regular courses, while 76% applied previous knowledge during the training. An average improvement of 17% in correct responses suggests that the playful exercise effectively facilitates the assimilation of key concepts in game theory among university students. This study underscores the potential of integrating active activities based on game theory to enrich the learning process in an academic context.

Few-shot temporal knowledge graph completion based on meta-optimization

Knowledge Graphs (KGs) have become an increasingly important part of artificial intelligence, and KGs have been widely used in artificial intelligence fields such as intelligent answering questions and personalized recommendation. Previous knowledge graph completion methods require a large number of samples for each relation. But in fact, in KGs, many relationships are long-tail relationships, and the existing researches on few-shot completion mainly focus on static knowledge graphs. In this paper, we consider few-shot completion in Temporal Knowledge Graphs (TKGs) where the event may only hold for a specific timestamp, and propose a model abbreviated as FTMO based on meta-optimization. In this model, we combine the time-based relational-aware heterogeneous neighbor encoder, the cyclic automatic aggregation network, and the matching network to complete the few-shot temporal knowledge graph. We compare our model with the baseline models, and the experimental results demostrate the performance advantages of our model.